Role: Sr. Snowflake Data Engineer (Python, DBT, Openflow)
Location: Remote.
Duration: Long Term.
Job Summary
We re hiring a Senior Snowflake Data Engineer to build and operate reliable, scalable data pipelines and curated data products on the Snowflake Data Cloud. Our platform uses a multi-account strategy, and our primary workloads support BI and ML/AI. This is a hands-on engineering role focused on Python-driven data engineering, robust ETL/ELT, and modern transformation practices using Streams, dbt Core and OpenFlow.
You ll partner with analytics, data science, platform, and security teams to deliver production-grade datasets with strong quality, observability, governance alignment, and performance/cost efficiency.
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Key Responsibilities
Build and maintain batch and/or near-real-time ETL/ELT pipelines landing data into Snowflake (raw curated consumption layers).
Develop Python data engineering components (connectors, orchestration logic, framework utilities, testing tools, and automation) supporting BI and ML use cases.
Implement transformation frameworks in dbt Core: project structure standards, modular models, macros, tests, documentation, and environment-based deployments.
Use OpenFlow to build and operationalize ingestion/flow patterns, including configuration, scheduling, troubleshooting, and performance tuning.
Design data models optimized for consumption: curated marts for BI, and ML-ready datasets/features with repeatable refresh patterns.
Apply data quality and reliability practices: automated testing, schema drift handling, idempotent loads, backfills, and reconciliation checks.
Tune Snowflake performance and cost for pipelines: warehouse sizing, clustering/partitioning strategy where appropriate, incremental processing, and query optimization.
Enable cross-account patterns aligned to the multi-account strategy (promotion between environments, sharing curated datasets, deployment consistency).
Build operational excellence: pipeline observability, alerting, runbooks, incident response participation, and root-cause analysis.
Collaborate with platform/security teams to align pipelines with governance controls (RBAC, secure data access patterns) without blocking delivery.
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Required Qualifications
15+ years of data engineering experience, including significant delivery on Snowflake in production.
Strong SQL and data modeling fundamentals (dimensional and/or domain-oriented modeling).
Hands-on experience with dbt Core (models, macros, tests, docs, deployments, CI practices).
Hands-on experience with OpenFlow (building/running flows, operational support, troubleshooting).
Proven experience designing and operating ETL/ELT pipelines (incremental loads, CDC concepts, error handling, and backfills).
Experience working in cloud environments (AWS/Azure/Google Cloud Platform) and production operations (monitoring, on-call/incident response, SLAs).
Comfortable working across teams (analytics, ML, platform/security) and translating requirements into deliverable datasets.
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Nice to Have
Experience supporting BI workloads (semantic-friendly marts, performance considerations, consumption patterns).
Experience supporting ML workflows (feature-ready datasets, reproducible training data, lineage and governance).
Familiarity with Snowflake governance features (masking/row access policies, secure views) and multi-account deployment patterns.
CI/CD and automation (Git workflows, build pipelines, infra-as-code such as Terraform).
Experience with common ingestion/orchestration tools (Airflow, Dagster, Prefect, etc.) or ELT tools (Fivetran/Matillion/Informatica).
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